Mapping fast tissue dynamics with long camera exposures via intensity modulation
Abstract
Measuring fast dynamic processes with dynamic light scattering over wide fields of view is critical for applications ranging from blood flow imaging to characterizing complex fluids, yet is often limited by the need for expensive, high frame rate cameras. Here, we introduce sinusoidal intensity modulation speckle imaging (SIMSI), a technique that overcomes this hardware limitation by encoding information about fast dynamics into images captured with long camera exposures. Within each exposure, we sinusoidally modulate the illumination intensity, yielding frequency selective speckle variance measurements that sample the power spectral density (PSD) of intensity fluctuations. By sweeping the modulation frequency across exposures, SIMSI maps the PSD while preserving high signal-to-noise long exposures. We fit the measured spectra with a flexible model and report a spectral cutoff frequency f c as a flow index. In controlled flow microfluidic phantoms, SIMSI PSD estimates agree with the reference PSD measurements from a coaligned high-speed detector, and the derived f c varies linearly with the imposed flow velocity ( R 2 > 0.999 ). In vivo in the mouse cortex, the SIMSI derived f c maps distinguish vascular compartments with distinct spectral signatures. Finally, SIMSI tracks the spatiotemporal evolution of cortical blood flow changes for ten days following ischemic stroke. SIMSI provides a robust and accessible method for wide field, frequency domain characterization of fast dynamics using standard cameras. This advance enables a richer characterization of complex systems and has wide ranging applications in biomedicine, engineering, and physics.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (7)
Hengfa Lu
Department of Biomedical Engineering
Qingwei Fang
Department of Biomedical Engineering
Jewel A. Ashbrook
Department of Biomedical Engineering
Victoria Nemchek
Psychology Department and Institute for Neuroscience
Michela Fracassi
Psychology Department and Institute for Neuroscience
Theresa A. Jones
Psychology Department and Institute for Neuroscience
Andrew K. Dunn
Department of Biomedical Engineering